package com.spring.agent.app;

import com.spring.agent.advisor.MyLoggerAdvisor;
import com.spring.agent.chatMemory.FileBasedChatMemory;
//import com.spring.agent.rag.QueryRewriter;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import static org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor.*;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
import org.springframework.ai.chat.client.advisor.QuestionAnswerAdvisor;
import org.springframework.ai.chat.client.advisor.SimpleLoggerAdvisor;
import org.springframework.ai.chat.client.advisor.api.Advisor;
import org.springframework.ai.chat.memory.ChatMemory;
import org.springframework.ai.chat.memory.InMemoryChatMemory;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.stereotype.Component;

import java.util.List;

@Component
@Slf4j
public class LoveApp {

    private final ChatClient chatClient;

    private static final String SYSTEM_PROMPT = "扮演深耕恋爱心理领域的专家。开场向用户表明身份，告知用户可倾诉恋爱难题。" +
            "围绕单身、恋爱、已婚三种状态提问：单身状态询问社交圈拓展及追求心仪对象的困扰；" +
            "恋爱状态询问沟通、习惯差异引发的矛盾；已婚状态询问家庭责任与亲属关系处理的问题。" +
            "引导用户详述事情经过、对方反应及自身想法，以便给出专属解决方案。";

    public LoveApp(ChatModel dashscopeChatModel) {
        // 基于内存的对话记忆
        ChatMemory chatMemory = new InMemoryChatMemory();
        // 基于文件的对话记忆
        String fileDir = System.getProperty("user.dir") + "/chat-memory";   // System.getProperty("user.dir")是Java中用于获取当前工作目录
        ChatMemory fileChatMemory = new FileBasedChatMemory(fileDir);

        chatClient = ChatClient.builder(dashscopeChatModel)
                .defaultSystem(SYSTEM_PROMPT)
                .defaultAdvisors(new MessageChatMemoryAdvisor(fileChatMemory),
                        // 自定义日志advisor
                        new MyLoggerAdvisor())
                .build();
    }

    public String doChat(String message,String chatId) {
        ChatResponse response = chatClient.prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY,chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY,10))
                .call()
                .chatResponse();
        String content = response.getResult().getOutput().getText();
        log.info("content:{}",content);
        return content;
    }

    // record 关键字所修饰的变量都是final的，不可以改变。
    public record LoveReport(String title, List<String> suggestions) {

    }

    /**
     * 生成恋爱报告
     */
    public LoveReport doChatWithReport(String message,String chatId) {
        LoveReport response = chatClient.prompt()
                .system(SYSTEM_PROMPT + "每次对话后都要生成恋爱结果，标题为{用户名}的恋爱报告，内容为建议列表")
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY,chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY,10))
                .call()
                .entity(LoveReport.class);
        log.info("content:{}",response);
        return response;
    }

    @Resource
    private VectorStore loveAppVectorStore;

    @Resource
    private Advisor loveAppRagCloudAdvisor;

    @Resource
    private VectorStore pgVectorVectorStore;

//    @Resource
//    private QueryRewriter queryRewriter;

    public String doChatWithRag(String message,String chatId) {
        // 执行查询重写
        //String rewritedMessage = queryRewriter.doQueryRewrite(message);

        ChatResponse response = chatClient.prompt()
                .user(message)
                .advisors(advisorSpec -> advisorSpec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                // 开启日志，便于观察
                .advisors(new MyLoggerAdvisor())
                // 应用RAG知识库问答(本地知识库)
                //.advisors(new QuestionAnswerAdvisor(loveAppVectorStore))
                // 应用RAG知识库问答(阿里云知识库)
                //.advisors(loveAppRagCloudAdvisor)
                // 应用 pgVectorStore 向量存储
                //.advisors(new QuestionAnswerAdvisor(pgVectorVectorStore))
                .call()
                .chatResponse();
        String content = response.getResult().getOutput().getText();
        log.info("content:{}",content);
        return content;
    }
}



















